Is it possible to rank search results based solely on proximity (and other filters) to a specific point and ignore the custom ranking formula (likes)?
For example, I'd like to rank results closest to times square strictly by distance and for the query to not care about the likes attribute.
I suppose the likes attributes is one of you own.
You can do what you need by removing the attribute like from the custom ranking.
If you need 2 way to search, you can do a replica index, with the same data but a different ranking formula: https://www.algolia.com/doc/guides/ranking/sorting/?language=go#multiple-sorting-strategies-for-an-index
Related
I have a database of users and each user record has "User ID" and "Group". After filtering out a chunk of the records, I'd like to sum the number of users within each group. Currently I am doing that with the calculation:
{FIXED[Group]:SUM([Number of Records])}
The problem here is this calculation appears to ignore any records that I've filtered out and just gives a total count per group from all of the unfiltered data.
Is there a quick way to sum the number of visible users in each group after applying a filter?
The easiest way of solving this would be to take advantage of the order of operations in Tableau.
The issue you are having at the moment is the LOD calculation is performed prior to a dimension filter.
If you want to calculate a field at a different level of detail then the view than a LOD is still the way to go. All you need to do is force tableau to apply the filters before calculating the fixed calculation.
In order to do this change your filters to a context filter. This is done by right clicking on the filter and selecting "Add to context. You will see the filter change from blue to grey.
Your calculated field should now be sensitive to any context filters.
Find out more here
I am trying to create a graph with two lines, with two filters from the same dimension.
I have a dimension which has 20+ values. I'd like one line to show data based on just one of the selected values and the other line to show a line excluding that same value.
I've tried the following:
-Creating a duplicate/copy dimension and filtering the original one with the first, and the copy with the 2nd. When I do this, the graphic disappears.
-Creating a calculated field that tries to split the measures up. This isn't letting me track the count.
I want this on the same axis; the best I've been able to do is create two sheets, one with the first filter and one with the 2nd, and stack them in a dashboard.
My end user wants the lines in the same visual, otherwise I'd be happy with the dashboard approach. Right now, though, I'd also like to know how to do this.
It is a little hard to tell exactly what you want to achieve, but the problem with filtering is common.
The principle that is important is that Tableau will filter the whole dataset by row. So duplicating the dimension you want to filter won't help as the filter on the original dimension will also filter the corresponding rows in the second dimension. Any solution has to be clever enough to work around this issue.
One solution is to build two new dimensions that use a calculation rather than a filter to create the new result. Let's say you have a dimension, [size] that has a range of numbers from 1 to 10 and you want to compare the total number of rows including and excluding the number 5. You could create a new field using a formula like if [size] <> 5 then 1 else 0 end
Summing the new field will give a count of the number of rows that don't contain a 5 and this can be compared directly to a rowcount of the original [size] field which will give the number including the value 5.
This basic principle can be extended to much more complex logic. The essential point is to realise that filters act on every row in your data and can't, by themselves, show comparisons with alternative filter choices on a single visualisation.
Depending on the nature of your problem there may be other solutions worth looking at including sets and groups but you would need to provide more specific details for users here to tell you whether they would be useful.
We can make a a set out of the values of the dimension and then place it in the required shelf. So, you will have your dimension which will plot accordingly and set which will have data as per the requirement because with filter you can't have that independence of showing data everytime you want.
I want to aggregate bins in tableau.
See the following figure:
I want to aggregate (merge) the NumberM from 6 untill 16 in one category. 5+/(6 and higher) for example and sum the values of 6-16 in that category. I think this can be done with a few simple clicks but I am not able to manage.
Thanks in advance,
Tim
There are several ways to classify data rows into different groups or classes: each with different strengths.
Create a calculated field As emh mentioned, one approach is to create a calculated field to assign a value to a new field indicating which group each data row belongs to. For the effect you want, the calculated field should be discrete (blue). If your calculation doesn't return a value for in one case, e.g. an if statement without an else clause, then the field will be null in that case which is a group in itself. This is a very general approach, and can handle much more complex cases. The only downsides are the need to maintain the calculated field definition and that the cutoff values are hard coded and by itself can't be changed dynamically via a control on the view. BUT those issues can by easily resolved by using a parameter instead of a numeric literal in your calculated field. In fact, that's probably the number one use case for parameters. If you think in SQL, a discrete field on a shelf is like a group by clause.
Use a filter If you only want a subset of the data in your view, e.g. data rows with NumberM in [6, 16] then you can drag the NumberM field onto the filters shelf and select the range you want. Note for continuous (green) numeric fields, filter ranges include their endpoints. Filters are very quick and easy to drop on a view. They can be made dynamically adjustable by right clicking on them and creating a quick filter. Its obvious from the view that a filter is in use, and the caption will include the filter settings in its description. But a filter doesn't let you define multiple bins. If you think in SQL, a filter is like a where clause (or in some cases using the condition tab, like a having clause)
Define histogram bins If you want to create regular sized bins to cover a numeric range, such as values in [1,5], [6,10], [11-15] ..., Tableau can create the bin field for you automatically. Just right click on a numeric field, and select Create Bins.
Define a group Very useful for aggregating discrete values, such as string fields, into categories. Good for rolling up detail or handling multiple spellings or variants in your data. Just right click on a field and select Create Group. Or select some discrete values on an axis or legend and press the paperclip option. If you then edit a group, you'll see what's going on. If you think in SQL, a group is like a SQL case statement.
Define a set Another way to roll up values. The definition of a set can be dynamically computed or a hard coded list of members. Both kinds are useful. You can combine sets with union, intersection, set difference operators, and can test set membership in calculated fields. Sets are useful for binary decisions, rows are divided into those that are members of the set and those that are not.
Filters, sets, groups, calculated fields and parameters can often be combined to accomplish different effects.
Most if not all of these features can be implemented using calculated fields, especially if the business rules get complicated. But if a filter, bin, group or set fits your problem well, then it's often best to start with that, rather than define a calculated field for each and every situation. That said, learning about the 4 kinds of calculated fields really makes a difference in being able to use Tableau well.
You can do this with calculated fields.
Go to: Select Analysis > Create Calculated Field.
Then use this formula:
IF NumberM > 5 THEN "OVER 5"
You can then use that calculated field as a filter on the worksheet in your screenshot.
Answering my own question:
With Tableau 9 this can be easily done with the increased flexibility of the level of detail expressions (LOD). I can really recommend this blog on that subject and many more Tableau functions.
Current Code: https://gist.github.com/anonymous/c1a178bc4118f850d9cd
The flaw here is that I have two indicies in the searchable alias. This means that I must use the same radius for both. I actually want to use a larger radius in the radius filter for one of the indicies. Is there any way to do this without having two separate calls to .prepareSearch, thus two separate hits to Elasticsearch
Sounds like your data might be better suited to being in one index, in which case you could use and/or filters to combine a geo distance filter with a type filter.
Another option would be to use the indicies query
The problem I'm trying to solve is finding the right similarity metric, rescorer heuristic and filtration level for my data. (I'm using 'filtration level' to mean the amount of ratings that a user or item must have associated with it to make it into the production database).
Setup
I'm using mahout's taste collaborative filtering framework. My data comes in the form of triplets where an item's rating are contained in the set {1,2,3,4,5}. I'm using an itemBased recommender atop a logLikelihood similarity metric. I filter out users who rate fewer than 20 items from the production dataset. RMSE looks good (1.17ish) and there is no data capping going on, but there is an odd behavior that is undesireable and borders on error-like.
Question
First Call -- Generate a 'top items' list with no info from the user. To do this I use, what I call, a Centered Sum:
for i in items
for r in i's ratings
sum += r - center
where center = (5+1)/2 , if you allow ratings in the scale of 1 to 5 for example
I use a centered sum instead of average ratings to generate a top items list mainly because I want the number of ratings that an item has received to factor into the ranking.
Second Call -- I ask for 9 similar items to each of the top items returned in the first call. For each top item I asked for similar items for, 7 out of 9 of the similar items returned are the same (as the similar items set returned for the other top items)!
Is it about time to try some rescoring? Maybe multiplying the similarity of two games by (number of co-rated items)/x, where x is tuned (around 50 or something to begin with).
Thanks in advance fellas
You are asking for 50 items similar to some item X. Then you look for 9 similar items for each of those 50. And most of them are the same. Why is that surprising? Similar items ought to be similar to the same other items.
What's a "centered" sum? ranking by sum rather than average still gives you a relatively similar output if the number of items in the sum for each calculation is roughly similar.
What problem are you trying to solve? Because none of this seems to have a bearing on the recommender system you describe that you're using and works. Log-likelihood similarity is not even based on ratings.